irtree_sim1: Generate data from and fit an ItemResponseTrees model
In hplieninger/ItemResponseTrees: IR-Tree Modeling in 'mirt', 'Mplus', or 'TAM'

Description Usage Arguments Value See Also

This function generates data from gen_model, subsequently fits all the models in fit_model, and returns the results and/or saves them to an external RData file.

irtree_sim1(
  R = 1,
  gen_model = NULL,
  fit_model = gen_model,
  N = NULL,
  sigma = NULL,
  itempar = NULL,
  link = c("logit", "probit"),
  na_okay = TRUE,
  engine = c("mirt", "mplus", "tam"),
  verbose = TRUE,
  control = NULL,
  improper_okay = FALSE,
  par_type = "difficulty",
  file = NULL,
  dir = tempdir(),
  save_rdata = FALSE,
  reduce_output = FALSE
)

`R`	Integer used to number the saved output if `save_rdata = TRUE`. Really only useful when used from `irtree_sim()`.
`gen_model`	Object of class `irtree_model` describing the data-generating model. See irtree_model for more information.
`fit_model`	Object of class `irtree_model` describing the model that should be fit to the data. May be a list of multiple objects of class `irtree_model` if different models should be fit to the same data set. See irtree_model for more information.
`N`	Integer, the number of persons.
`sigma`	Either a matrix or a function that returns a matrix. This matrix is the variance-covariance matrix of the person parameters that is passed to `MASS::mvrnorm()`. Note that the order of the person parameters is taken from the section Processes in the model `object` (see irtree_model).
`itempar`	Either a list or a function that returns a list. The list has an element `beta` and an element `alpha`. Each of these is a matrix of item parameters. Note that the order of items (rows) is taken from the section Items and the order of processes (columns) is taken from the section Processes in the `model` (see irtree_model).
`link`	Character. Link function to use.
`na_okay`	Logical indicating whether variables with unobserved response categories are permitted. If `FALSE`, rejection sampling is used to ensure that all categories are observed.
`engine`	String specifying whether to use mirt, Mplus, or TAM for estimation.
`verbose`	Logical indicating whether output should be printed to the console.
`control`	List. The allowed elements of this list depend on the `engine`. Use `control_mirt()`, `control_mplus()`, or `control_tam()` for convenience. Note that the `fit()` function does not use `...`, but that you can use the `control_*()` functions to pass additional arguments.
`improper_okay`	Logical indicating whether the model should also be fit if it is not a proper IR-tree model. Set this only to `TRUE` if you really know what you are doing.
`par_type`	Only used if the fit engine was mirt. Item parameters (or thresholds) can be either of type `easiness` (the mirt default) or `difficulty` (as in Mplus and TAM).
`file`	String giving the file path used to save the output if `save_rdata = TRUE`. Note that the file ending is automatically set to `.rda`. This argument is also passed to `irtree_fit_mplus()` if applicable.
`dir`	Path name that is used to save the results of every run if `save_rdata = TRUE`.
`save_rdata`	Logical indicating whether to save the results to an RData file.
`reduce_output`	Logical indicating whether the returned object should be reduced (i.e., the output of `fit()` is removed and only summary information is retained).

List with two elements. The second element spec contains various arguments (such as the data). The first element fits is a list with one element for each fit_model that contains the output of fit() as well as the elements glanced, tidied, and augmented (see glance(), tidy(), and augment()).